Open Access

Within the last 30 years the role of nitrogen in Central European forests has changed fundamentally from limiting resource to environmental problem. As the retrospective tracking of nutrient availability by soil chemical and biogeochemical measurements faces serious problems, bioindication based on understorey species composition is indispensable for monitoring broad-scale eutrophication. Based on a broad survey of more than 100,000 forest vegetation plots accessible in electronic data-bases from Germany and adjacent countries, we calculated unweighted average Ellenberg nutrient values (mN) as a proxy of plant-available macronutrients. Based on the quantiles of the frequency distribution of mN in a regionally stratified sample, we define five trophic classes, which can be used to compare dimensionless mN values. We studied spatial patterns of average nutrient values within 17 regions and compared the periods from 1899 to 1975 and 1976 to 2006. After 1975 eutrophic (mN > 5.67) and hypertrophic (mN > 6.28) conditions were common everywhere except in the Alps and Saxony-Anhalt, but very oligotrophic conditions (mN < 3.44) were still widespread in regions with nutrient-poor bedrock. Before 1975 mN of plots had been lower than after 1975 in all but the southeastern regions. Between the pre- and post-1975 data the proportion of hypertrophic plots increased from 5.7 to 11.8%, and that of very oligo-trophic plots decreased from 14.6 to 8.3%. To remove bias resulting from uneven distribution, the dataset was stratified by five tree layer dominance types, period and region and resampled. In pre-1975 plots medians of mN increased in the order Pinus sylvestris, Quercus spp., Picea abies, Fagus sylvatica and Alnus spp, whereas the increase of mN was highest in forest types with historically low nutrient values. Therefore, the widespread change in mN must be attributed to the pronounced vegetation changes in Quercus and Pinus stands, indicating the importance of land-use change, i.e. recovery of nutrient cycles after hundreds of years of exploitation through coppicing, grazing and litter use. The analysis confirms eutrophication as a megatrend of modern vegetation change and demonstrates the high research potential of linking vegetation plot databases across large regions.

Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.

Der Global Index of Vegetation-Plot Databases (GIVD) ist eine Metadatenbank von Vegetations - datenbanken weltweit, die im Jahr 2010 von einem internationalen Leitungsgremium ins Leben gerufen wurde und auf einem Server in Greifswald beheimatet ist. Ziel von GIVD ist es, einen besseren Überblick über die zunehmende Zahl von Vegetationsdatenbanken zu geben und ihren Inhalt für übergreifende vegetationsökologische Analysen zu erschließen. Im vorliegenden Beitrag analysieren wir, welche Daten aus Mitteleuropa (incl. Benelux-Länder) in GIVD derzeit registriert sind. Am 20. März 2011 stammten 1,35 Millionen der insgesamt registrierten 2,45 Millionen Vegetationsaufnahmen aus den 12 betrachteten Ländern. Mit über 600.000 digital verfügbaren Vegetationsaufnahmen entsprechend einer Dichte von 18 km–2 sind die Niederlande weltweit führend.